Finding Where AI Fits

Before you can find where AI fits, you need a clear picture of how work actually flows through your organization. We guide your team through a structured workflow mapping exercise that captures your key processes, the people involved, the tools you use, and the pain points that slow things down.

We also surface something official process maps rarely capture: the human experience of the workflow. Where do staff feel frustrated? Where have they developed informal workarounds? Where have they quietly stopped following the documented process? That tacit knowledge is often where the most valuable AI opportunities are hiding, and this exercise is designed to bring it to the surface. This map becomes the foundation for everything that follows.

Not every workflow is a good candidate for AI. We introduce a diagnostic framework that evaluates each process against key criteria: task volume and repetitiveness, data availability and quality, current time and cost, error frequency, and strategic importance. We also add an equity and disparate impact criterion for workflows that touch clients or community members, asking whether applying AI could produce biased or inequitable outcomes for the people served.

The diagnostic also names workflows that should not use AI at all, not because they fail on volume or data, but because the values or trust stakes are too high. You will finish with a clear picture of your strong candidates, your borderline cases, and your firm boundaries.

Once you know which workflows could benefit from AI, the question becomes where to start. We use a prioritization matrix that plots each opportunity by mission impact, feasibility given current resources, and stakeholder alignment. That third dimension asks whether clients, funders, community members, and staff want AI involved in this part of the work. Their needs, preferences, and trust are constraints that belong in your prioritization from the start.

Rather than chasing quick wins that can set unrealistic expectations, this exercise helps your team sequence opportunities as a learning progression, with each implementation informing the next and building organizational knowledge and confidence rather than just checking boxes.

Different workflows call for different AI approaches. We walk through the categories of AI tools available today: generative AI for content and communication, predictive models for data analysis, automation platforms for repetitive tasks, and conversational agents for stakeholder interactions. For each of your priority workflows, you will identify the type of AI solution that fits best.

Because the tool landscape changes faster than any workshop can keep up with, we also give you a simple evaluation framework for assessing tools you have not encountered yet. A set of questions you can ask about any new AI tool, regardless of what it is called or how it is marketed, that helps you determine whether it genuinely fits your workflow, your data environment, and your values.

We close by assembling your work into a complete opportunity map: a visual, prioritized guide showing where AI fits in your organization, what tools are best suited for each opportunity, and a suggested sequence for implementation. Each opportunity is evaluated on impact, feasibility, mission alignment, and stakeholder support, so what you leave with reflects not only what AI can do, but what it should do given your values and the people you serve.

For opportunities that touch clients or community members directly, the map also identifies where a participatory validation step belongs before implementation begins. This is what separates an opportunity map that gets used from one that drives decisions people later regret.